A Business Zone Recommender System Based on Facebook and Urban Planning Data
This work addresses the problem of business location selection for entrepreneurs or urban planners in specific cities, but it is incremental as it applies existing machine learning methods to new data sources.
The authors tackled the problem of recommending urban zones for physical businesses by developing ZoneRec, a system that uses Facebook and urban planning data, and they evaluated it on food businesses in Singapore, assessing feature contributions to recommendation quality.
We present ZoneRec---a zone recommendation system for physical businesses in an urban city, which uses both public business data from Facebook and urban planning data. The system consists of machine learning algorithms that take in a business' metadata and outputs a list of recommended zones to establish the business in. We evaluate our system using data of food businesses in Singapore and assess the contribution of different feature groups to the recommendation quality.